title: Estimating inputs and an internal neuronal parameter from a single spike train.
abstract: Because neurons are integrating input signals and translating them into timed output spikes, examining spike timing may reveal information about inputs, such as population activities of excitatory and inhibitory presynaptic neurons. Here we construct a state-space method for estimating not only such extrinsic parameters, but also an intrinsic neuronal parameter such as the membrane time constant from a single spike train.
authors.forename: Shigeru
authors.initials: S
authors.lastname: Shinomoto
authors.forename: Hideaki
authors.initials: H
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019706:Excitatory Postsynaptic Potentials; D053444:Inhibitory Postsynaptic Potentials; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*